The standard VAE model assumes that the joint distribution factorises across the samples. On the other hand, GPs are well-suited to model these correlations.
Extension of VAEs, such as GPPVAE [1]}, GP-VAE [2]} and L-VAE [3]}, combine VAEs with GPs.
These methods use a GP prior (instead of a standard Gaussian prior) in the latent space of a VAE to model multivariate temporal and longitudinal data.
